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    Changing Careers? This Is How to Defeat the Sunk Cost Fallacy, with Doctor-turned-developer Shona

    enSeptember 26, 2023
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    About this Episode

    ๐ŸŽ™ About the episode

    Meet Shona Chan ๐Ÿ‡ธ๐Ÿ‡ฌ๐Ÿ‡ฌ๐Ÿ‡ง! Shona was an anesthesiologist. Now, she's a developer. It all started when she wanted to write an app to solve a problem she had at work as a doctor. One thing led to another, and eventually, she took the plunge into coding, realizing that a career switch might not be such a bad idea.

    This is a story of intrinsic motivation, amazing portfolio projects, and landing a job without even having to go through a tech interview. You'll discover how to identify your purpose, find out how to muster enough motivation to tackle difficult decisions, and learn why Shona saw her career change as a lateral move instead of a fresh start. Shona reveals what ten years in medicine taught her and how that relates to her new career If you listen to the end, you will get some fantastic ideas to integrate into your study plan or job-hunting strategy. Plus, you'll find out the ideal music for a cesarean section.

    ๐Ÿ”— Connect with Shona

    โฐ Timestamps

    • Shona never thought she would code for a living, although she did play Neopets (02:13)
    • How Shona started coding because she wanted to solve a real-world work problem she had as a doctor (02:58)
    • Shona's career in medicine (05:48)
    • Community Break with Jan the Producer (09:55)
    • Why Shona eventually wanted to switch careers, and did it feel weird after dedicating so many years to medicine? (11:47)
    • What skills Shona learned as a doctor helped her become a developer? (14:01)
    • Doctors on TV vs. programmers on TV (14:55)
    • Learning to code on YouTube, and when does it become not enough? (15:46)
    • How Shona enrolled into a bootcamp (18:26)
    • Why did Shona feel like she needed to give coding a go? (21:35)
    • Quick-fire questions: Lo-fi Disney and the perfect music for a C-section (23:02)
    • Shona's new role in a health tech startup (26:03)
    • When did Shona feel ready to apply for jobs? (Also, her portfolio projects are amazing. )(27:26)
    • Shona's cold email that brought her a job (31:05)
    • Shona got hired without a tech interview (32:55)
    • Why unique projects are never a waste of time (33:55)
    • Start networking earlier than you think! (35:28)
    • How Scrimba podcast helped Shona with her career change (36:12)
    • How to deal with sunk cost fallacy (38:53)

    ๐Ÿงฐ Resources Mentioned

    โญ๏ธ Leave a Review


    If you enjoyed this episode, please leave a 5-star review here and tell us who you want to see on the next podcast.
    You can also Tweet Alex from Scrimba at @bookercodes and tell them what lessons you learned from the episode so that he can thank you personally for tuning in ๐Ÿ™ Or tell Jan he's butchered your name here.




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    ๐Ÿงฐ Resources Mentioned

    โญ๏ธ Leave a Review


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    ๐Ÿงฐ Resources Mentioned

    โญ๏ธ Leave a Review


    If you enjoyed this episode, please leave a 5-star review here and tell us who you want to see on the next podcast.
    You can also Tweet Alex from Scrimba at @bookercodes and tell them what lessons you learned from the episode so that he can thank you personally for tuning in ๐Ÿ™ Or tell Jan he's butchered your name here.

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    ๐ŸŽ™ About the episode


    Meet Cassie Lewis ๐Ÿ‡บ๐Ÿ‡ธ! Cassie has a fine arts degree, which turned out to be too fancy for the real world. After working in different fields, from photography to retail, she got interested in coding - and it turned out to be just the right fit with how her mind works! Cassie is fueled by curiosity, creativity, and challenges. And learning to code alongside a day job was certainly a challenge.

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    ๐Ÿ”— Connect with Cassie

    โฐ Timestamps

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    ๐Ÿงฐ Resources Mentioned

    โญ๏ธ Leave a Review


    If you enjoyed this episode, please leave a 5-star review here and tell us who you want to see on the next podcast.
    You can also Tweet Alex from Scrimba at @bookercodes and tell them what lessons you learned from the episode so that he can thank you personally for tuning in ๐Ÿ™ Or tell Jan he's butchered your name here.



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    ๐ŸŽ™ About the episode


    Meet Bob Ziroll ๐Ÿ‡บ๐Ÿ‡ธ! Bob is Scrimba's Head of Education and one of the Internet's favorite React teachers. His latest course is on AI, but don't worry, there's React... I mean, ReAct in AI as well!

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    Bob's AI agents and automation course is part of Scrimba's brand-new AI path. Let's dive in!


    This is the final episode of our series on AI engineering, introducing Scrimba's AI Engineer Path. This path is your gateway to unlocking the full potential of AI for your projects.

    ๐Ÿ”— Connect with Bob

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    • AI is moving even faster than the front end (02:16)
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    • ChatGPT vs. the GPT foundation model (04:15)
    • What is an AI agent (05:45)
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    • Midroll! (11:56)
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    • How can you build your own AI agent? (24:34)
    • React... and REact (31:26)
    • Advice on how to stay up-to-date without getting totally overwhelmed (35:58)

    ๐Ÿงฐ Resources Mentioned

    โญ๏ธ Leave a Review


    If you enjoyed this episode, please leave a 5-star review here and tell us who you want to see on the next podcast.
    You can also Tweet Alex from Scrimba at @bookercodes and tell them what lessons you learned from the episode so that he can thank you personally for tuning in ๐Ÿ™ Or tell Jan he's butchered your name here.



    What Is Retrieval-Augmented Generation and How to Make AI Work for You, with Guil Hernandez

    What Is Retrieval-Augmented Generation and How to Make AI Work for You, with Guil Hernandez

    ๐ŸŽ™ About the episode


    Meet Guil Hernandez ๐Ÿ‡บ๐Ÿ‡ธ! He is a developer and educator with over 15 years of experience in tech. He's also a Scrimba teacher who is a part of the team bringing you the AI Engineer Path, and in this episode, he's helping us understand retrieval-augmented generation.

    In the previous episode, Tom Chant helped us understand the world of AI models. Today, Guil will further teach us how these models work under the hood. AI models don't understand the world like we do. When we interact with them, they turn our inputs into mathematical representations known as embeddings. By creating our own embeddings, we can teach AI to do what we want it to.

    Today, we're getting an introduction about making a model aware of your own data source so that that data can be considered for the AI output. For example, using the techniques you'll learn from Guil in this episode, you could connect a model to your customer support conversations so that the model knows what is necessary to answer unique questions about your (or your client's) business.

    This is the third episode of our series on AI engineering, introducing Scrimba's AI Engineer Path. This path is your gateway to unlocking the full potential of AI for your projects.

    ๐Ÿ”— Connect with Guil

    โฐ Timestamps

    • Guil focuses on RAG and embeddings (01:42)
    • RAG makes a foundation model aware of your data (03:14)
    • Spotify has been using RAG since 2014 (05:56)
    • How embedding works: embedding model + vector database + generative model (09:00)
    • You're enhancing content retrieved from a database with a generative model (10:26)
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    • What's a vector database? (12:35)
    • Can we make an AI chatbot for the Scrimba podcast? (15:05)
    • You can chunk the files directly at OpenAI now! (16:49)
    • OpenAI's Assistants API (17:33)
    • AI is evolving quickly (19:07)
    • Assistants API does RAG (19:55)
    • What is fine-tuning? (20:39)
    • Differences between RAG and fine-tuning (21:14)
    • Community break with Jan the Producer (23:58)


    ๐Ÿงฐ Resources Mentioned

    โญ๏ธ Leave a Review


    If you enjoyed this episode, please leave a 5-star review here and tell us who you want to see on the next podcast.
    You can also Tweet Alex from Scrimba at @bookercodes and tell them what lessons you learned from the episode so that he can thank you personally for tuning in ๐Ÿ™ Or tell Jan he's butchered your name here.

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